extensions of recurrent neural network language model

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Ngày tải lên: 08/07/2014, 17:02

... using neural networks. In the first part, in-depth surveys of recent progress of neural network computing paradigms are presented. Part One consists of five chapters: • Chapter 1: Introduction to Neural ... extension of the conventional PCA. • Chapter 9: Applications of Artificial Neural Networks to Time Series Prediction. In this chapter, Liao, Moody, and Wu provide a technical overview of neural network approaches ... important application of artificial neural networks. In fact, a majority of neural network applications can be categorized as solving complex pattern classification problems. In the area of signal processing,...

Ngày tải lên: 12/12/2013, 23:15

... contents of this book. 1.2 Artificial Neural Network (ANN) Models — An Overview 1.2.1 Basic Neural Network Components A neural network is a general mathematical computing paradigm that models the ... graph consists of nodes (in the case of a neural network, neurons, as well as external inputs) and directed arcs (in the case of a neural network, synaptic links). The topology of the graph can ... a neural network with cyclic topology contains at least one cycle formed by directed arcs. Such a neural network is also known as a recurrent network. Due to the feedback loop, a recurrent network...

Ngày tải lên: 12/12/2013, 23:15

Ngày tải lên: 29/12/2013, 11:17

... and comparison of models. Journal of Geophysical Research 90 (C5), 8995–9005. Yao, X., 1999. Evolving artificial neural networks. Proceedings of the IEEE Transactions on Neural Networks 87 (9), ... 15) Generation 150 Selection of parents using stochastic universal sampling Competition of populations was not utilised Migration within the interval of 15 gen. and rate of 0.1 Reinsertion of offsprings with ... stated the evolving of model inputs and high-level architecture itself could not improve the performances of the models significantly. However, more robust and reasonable models were produced,...

Ngày tải lên: 17/02/2014, 22:20

... the f-score outperform state -of- the-art models re- 709 mary corpus for our model. The language model part of the noisy channel model already uses a bi- gram language model based on Switchboard, ... detail. 5.2 Language Model Informally, the task of language model component of the noisy channel model is to assess fluency of the sentence with disfluency removed. Ideally we would like to have a model ... of a variety of language models trained from text or speech corpora of vari- ous genres and sizes. The largest available language models are based on written text: we investigate the effect of...

Ngày tải lên: 20/02/2014, 04:20

... Estimating Probabilities of English Bigrams. Computer Speech & Language, 5(1):19–54. Joshua Goodman. 2001. A Bit of Progress in Language Modeling. Computer Speech & Language, 15(4):403– 434. Bo-June ... Improved Backing-off for M-Gram Language Modeling. In Pro- ceedings of International Conference on Acoustics, Speech, and Signal Processing. Robert C. Moore and William Lewis. 2010. Intelligent selection of language ... k train (w) denote the number of occurrences of w in the training corpus, and k test (w) denote the number of occurrences of w in the test corpus. We define the empirical discount of w to be d(w) = k train (w)...

Ngày tải lên: 20/02/2014, 04:20

... empirical study of smoothing techniques for language model- ing. Computer Speech and Language, 13:359–394. Joshua T. Goodman. 2001. A bit of progress in lan- guage modeling. Computer Speech and Language, 15:403–434. Slava ... FSTs of differ- ent sizes. The FSTs contain the acoustic models, language model and lexicon, but the LM makes up for most of the size. The availability of data varies for the different languages, ... size of the web mixture LM is limited to the size of the baseline in-domain LM. 1 Introduction An automatic speech recognition (ASR) system consists of acoustic models of speech sounds and of a...

Ngày tải lên: 22/02/2014, 02:20

... out because of technical problems in terms of the speed of the network and the reliability of the software. Another challenge to the use and implementation of computer- assisted language learning ... disadvantages of using computer network technology in language teaching Vu Tuong Vi (*) (*) MA., Department of English-American Language and Culture, College of Foreign Languages - VNU. ... of second/foreign language. Indeed, the use of the Internet and the World Wide Web in second and foreign language instruction has been increasingly recognized. A number of applications of...

Ngày tải lên: 05/03/2014, 12:20

... according to a language model trained on I, of a text segment s drawn from N. Let H N (s) be the per-word cross-entropy of s according to a language model trained on a ran- dom sample of N. We partition ... domain- specific and non-domain-specifc language models, for each sentence of the text source used to produce the latter language model. We show that this produces better language models, trained on less data, ... for each of these modifed language models is compared to that of the orig- inal version of the model in Table 2. It can be seen that adjusting the vocabulary in this way, so that all models are...

Ngày tải lên: 07/03/2014, 22:20

... Linguistics The use of formal language models in the typology of the morphology of Amerindian languages Andr ´ es Osvaldo Porta Universidad de Buenos Aires hugporta@yahoo.com.ar Abstract The aim of this ... some preliminary results of an investigation in course on the typology of the morphol- ogy of the native South American lan- guages from the point of view of the for- mal language theory. With this ... examples of de- scriptions of two Aboriginal languages fi- nite verb forms morphology: Argentinean Quechua (quichua santiague˜no) and Toba. The description of the morphology of the finite verb forms of...

Ngày tải lên: 07/03/2014, 22:20

... i i i ! (DEP model) o (TRI model) "*' rT I I I I I I 200 400 600 800 1000 1200 1400 1600 No. of training sentences Figure 8: Model size Related to the size of model, however, ... more useful than the naive word sequences of n-gram, for language modeling. We are planning to experiment the perfor- mance of the proposed language model for large corpus, for various domains, ... Based n-gram Models of Natural Language& quot;. Computational Linguistics, 18(4):467-480. C. Chang and C. Chen. 1996. "Application Is- sues of SA-class Bigram Language Models"....

Ngày tải lên: 08/03/2014, 05:21

... a statistical language model and a measure of tense difficulty. 4.1 The language model The lexical difficulty of a text is quite an elaborate phenomenon to parameterise. The logistic regres- sion models ... fact that the MLR model multiplies the number of pa- rameters by J − 1 compared to the PO model. Because of this, they recommend using the PO model. 6 Implementation of the models Having covered ... presented a variation of a multinomial naive Bayesian classifier they called the “Smoothed Unigram” model. We retained from their work the use of language models in- stead of word lists to measure...

Ngày tải lên: 08/03/2014, 21:20

... discriminative lan- guage models. First, we introduced the idea of us- ing factored features in the discriminative language modeling framework. Factored features allow the language model to capture linguistic ... generative language models have been extended in several ways. Generative factored language models (Bilmes and Kirchhoff, 2003) represent each token by multiple factors – such as part -of- speech, ... a tri- gram generative language model with Kneser-Ney smoothing. We then obtain training data for the dis- criminative language model as follows. We take a random subset of the parallel training...

Ngày tải lên: 17/03/2014, 00:20